How can semantic annotation help us to analyse the discourse of climate change in online user comments?
User comments in response to newspaper articles published online offer a unique resource for studying online discourse. The number of comments that articles often elicit poses many methodological challenges and analyses of online user comments have inevitably been cursory when limited to a manual co...
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| Format: | Article |
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Bern Open Publishing
2015
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| Online Access: | https://eprints.nottingham.ac.uk/37493/ |
| _version_ | 1848795470839676928 |
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| author | Collins, Luke C. |
| author_facet | Collins, Luke C. |
| author_sort | Collins, Luke C. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | User comments in response to newspaper articles published online offer a unique resource for studying online discourse. The number of comments that articles often elicit poses many methodological challenges and analyses of online user comments have inevitably been cursory when limited to a manual content or thematic analysis. Corpus analysis tools can systematically identify features such as keywords in large datasets. This article reports on the semantic annotation feature of the corpus analysis tool Wmatrix which also allows us to identify key semantic domains. Building on this feature, I introduce a novel method of sampling key comments through an examination of user comment threads taken from The Guardian website on the topic of climate change. |
| first_indexed | 2025-11-14T19:32:36Z |
| format | Article |
| id | nottingham-37493 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:32:36Z |
| publishDate | 2015 |
| publisher | Bern Open Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-374932020-05-04T17:05:07Z https://eprints.nottingham.ac.uk/37493/ How can semantic annotation help us to analyse the discourse of climate change in online user comments? Collins, Luke C. User comments in response to newspaper articles published online offer a unique resource for studying online discourse. The number of comments that articles often elicit poses many methodological challenges and analyses of online user comments have inevitably been cursory when limited to a manual content or thematic analysis. Corpus analysis tools can systematically identify features such as keywords in large datasets. This article reports on the semantic annotation feature of the corpus analysis tool Wmatrix which also allows us to identify key semantic domains. Building on this feature, I introduce a novel method of sampling key comments through an examination of user comment threads taken from The Guardian website on the topic of climate change. Bern Open Publishing 2015-03-03 Article PeerReviewed Collins, Luke C. (2015) How can semantic annotation help us to analyse the discourse of climate change in online user comments? Linguistik Online, 70 (1). pp. 43-60. ISSN 1615-3014 https://bop.unibe.ch/linguistik-online/article/view/1743/2957 doi:10.13092/lo.70.1743 doi:10.13092/lo.70.1743 |
| spellingShingle | Collins, Luke C. How can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| title | How can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| title_full | How can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| title_fullStr | How can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| title_full_unstemmed | How can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| title_short | How can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| title_sort | how can semantic annotation help us to analyse the discourse of climate change in online user comments? |
| url | https://eprints.nottingham.ac.uk/37493/ https://eprints.nottingham.ac.uk/37493/ https://eprints.nottingham.ac.uk/37493/ |